Instructions to use usyd-community/vitpose-plus-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use usyd-community/vitpose-plus-large with Transformers:
# Load model directly from transformers import AutoImageProcessor, VitPoseForPoseEstimation processor = AutoImageProcessor.from_pretrained("usyd-community/vitpose-plus-large") model = VitPoseForPoseEstimation.from_pretrained("usyd-community/vitpose-plus-large") - Notebooks
- Google Colab
- Kaggle
vitpose-plus COCO-wholebody keypoints
#2
by TomVanWouwe - opened
My understandig was that setting the dataset_index to "5" would lead to getting the richer COCO-wholebody keypoints.
However, when setting dataset_index to "5", the output remains 17 keypoints. There also seems to be something wrong (see images).
Is this currently not supported or am I missing something?
